There are many applications for determining three-dimensional object information from pairs or sets of two-dimensional images that each capture a particular scene from different angles. Stereo image matching is a type of such processing that has a goal of determining a disparity map between image pairs that are taken of the same scene. Due to its ill-posed nature, the major challenges of stereo matching involve finding the correct disparity for pixels that are within areas of: (1) textureless regions, (2) depth discontinuous boundaries and (3) occluded portions of the images. These challenges reduce the robustness of information determined by these stereo image matching techniques, and reduce the usability of the three-dimensional data they produce.
Therefore a need exists to overcome the problems with the prior art as discussed above.